2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2024
Provable Policy Gradient Methods for Average-Reward Markov Potential Games
Min Cheng, Ruida Zhou, P. R. Kumar +1
We study Markov potential games under the infinite horizon average reward criterion. Most previous studies have been for discounted rewards. We prove that both algorithms based on…
cs.LG2023★ 2 cited
Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games
Youbang Sun, Tao Liu, Ruida Zhou +2
This work studies an independent natural policy gradient (NPG) algorithm for the multi-agent reinforcement learning problem in Markov potential games. It is shown that, under mild…